Frequency count for "Sales" department: 12
import plotly.express as px
import pandas as pd
# -----------------------
# Dataset (with 12 "Sales")
# -----------------------
departments = [
"Finance", "Marketing", "IT", "HR",
"Sales", "Sales", "Sales", "Sales", "Sales", "Sales",
"Sales", "Sales", "Sales", "Sales", "Sales", "Sales", # 12 total
"Finance", "Marketing", "IT", "HR", "Finance", "IT"
]
df = pd.DataFrame({"Department": departments})
# -----------------------
# Plotly Histogram
# -----------------------
fig = px.histogram(
df,
x="Department",
title="Department Distribution"
)
# -----------------------
# Save HTML
# -----------------------
output_file = "output.html"
fig.write_html(output_file)
# -----------------------
# Extra info to inject
# -----------------------
roll_email = "24f1001831@ds.study.iitm.ac.in"
sales_count = (df["Department"] == "Sales").sum()
injection = f"""
Roll Number / Email: {roll_email}
Frequency count for "Sales" department: {sales_count}
"""
# -----------------------
# Read back own script
# -----------------------
with open(__file__, "r", encoding="utf-8") as f:
script_content = f.read()
code_block = f"""
Python Code Used:
{script_content}
"""
# -----------------------
# Modify HTML file
# -----------------------
with open(output_file, "r", encoding="utf-8") as f:
html = f.read()
html = html.replace("", injection + code_block + "") with open(output_file, "w", encoding="utf-8") as f: f.write(html) print(f"✅ HTML file generated: {output_file}") print(f" 'Sales' frequency = {sales_count}")
import matplotlib.pyplot as plt
import seaborn as sns
# proof-of-work (same as in the script):
# sns.countplot(x="Department", data=df)
# plt.title("Department Distribution (seaborn)")